Posts tonen met het label Artifical Intelligence. Alle posts tonen
Posts tonen met het label Artifical Intelligence. Alle posts tonen

donderdag 19 september 2019

Enterprise Architectures for Artificial Intelligence (I)


In the past three decades, I have seen artificial intelligence (AI) coming and going a couple of times. From studying MYCIN via speech technology in Flanders Language Valley to today’s machine learning and heuristics as used by Textgain from Antwerp University, the technology is here to stay this time.
Why? Because the cost of using AI has fallen dramatically not just in terms of hard and software but also in terms of acquiring the necessary knowledge to master the discipline.
Yet, most of the AI initiatives are still very much in the R&D phase or are used in limited scope. But here and there, e.g. in big (online) retail and telecommunications, AI is gaining traction on enterprise level.  And through APIs, open data and other initiatives, AI will become available for smaller organisations in the near future.
To make sure this effort has a maximum chance of success, CIOs need to embed this technology in an enterprise architecture covering all aspects: motivations, objectives, requirements and constraints, business processes, applications and data.
Being fully aware that I am trodding on uncharted territory, this article is –for now- my state of the art.

Introducing AI in the capability map

AI will enhance our capabilities in all areas of Treacy & Wiersema’s model, probably in a certain order. First comes operational excellence as processes and procedures are easier to describe, measure and monitor. Customer intimacy is the next frontier as the existing discipline of customer analytics lays the foundation for smarter interactions with customers and prospects.
The toughest challenge is in the realm of product leadership. This is an area where creativity is key to success. There is an approximation of creativity using what I call “property exploration” where a dimensional model of all possible properties of a product, a service, a marketing or production plan are mapped and an automatic cartesian product of all levels or degrees of each property with all the other properties is evaluated for cost and effectiveness. Sales pitch: if you want more information about this approach, contact us.

Capabilities and AI
Capabilities where state of the art AI can play a significant role
Examples of capabilities where AI can play a defining role. Some of these capabilities are already well supported, to name a few: inventory management (automatic replenishment and dynamic storage), cycle time management (optimising man-machine interactions), quality management (visual inspection systems), churn management (churn prediction and avoidance in CRM systems), yield management (price, customer loyalty, revenue and capacity optimisation) and talent management (mining competences from CVs).

Areas where AI is coming of age: loyalty management and competitive intelligence, R & D management and product development.

In the next post I will discuss a generic architecture for AI in support of primary processes; Stay tuned and… share your insights on this topic!